1. Genetic Data from Nearly 63,000 Women of European Descent Predicts DNA Methylation Biomarkers and Epithelial Ovarian Cancer Risk
- Author
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Usha Menon, Ralf Bützow, Siddhartha Kar, Jonathan Tyrer, Francesmary Modugno, Ellen L. Goode, Diana Eccles, Cristina Rodríguez-Antona, Renée T. Fortner, Linda E. Kelemen, Elio Riboli, Javier Benitez, Taymaa May, Kexin Chen, David G. Huntsman, Susana Banerjee, Penelope M. Webb, Rosalind Glasspool, Hoda Anton-Culver, Andrew Berchuck, Emily White, Thilo Dörk, Lang Wu, Douglas A. Levine, Heli Nevanlinna, Anita Koushik, Joe Dennis, Veronica Wendy Setiawan, Walter C. Willett, Yingchang Lu, Håkan Olsson, Nicolas Wentzensen, Kang Shan, Holly R. Harris, N. Charlotte Onland-Moret, Claus Høgdall, Jennifer A. Doherty, Fei Ye, Yaohua Yang, Qiuyin Cai, Linda S. Cook, Jacek Gronwald, Keitaro Matsuo, Joellen M. Schildkraut, James D. Brenton, Isabelle Romieu, Shelley S. Tworoger, Anna H. Wu, Alvaro N.A. Monteiro, Roberta B. Ness, Paul D.P. Pharoah, James Paul, Alicia Beeghly-Fadiel, Wei Zheng, Lambertus A. Kiemeney, Rebecca Sutphen, Thomas A. Sellers, Michelle A.T. Hildebrandt, Yin Ling Woo, Simon A. Gayther, Meir J. Stampfer, Diether Lambrechts, Marc T. Goodman, Weiva Sieh, Line Bjørge, Lukasz Szafron, Leon F.A.G. Massuger, Daniel W. Cramer, Bingshan Li, Susan J. Ramus, Nadeem Siddiqui, Dale P. Sandler, Jirong Long, Peter A. Fasching, Tanja Pejovic, Drakoulis Yannoukakos, Florian Heitz, Beth Y. Karlan, Estrid Høgdall, Malcolm C. Pike, Anthony J. Swerdlow, Georgia Chenevix-Trench, Catherine M. Phelan, Xiang Shu, Digna R. Velez Edwards, Celeste Leigh Pearce, Sue K. Park, Patricia G. Moorman, Soo-Hwang Teo, Nhu D. Le, Susanne K. Kjaer, Kirsten B. Moysich, Graham G. Giles, Alicja Wolk, Iain A. McNeish, Xiao-Ou Shu, Jenny Chang-Claude, L Yan, Anna deFazio, Ian G. Campbell, HUSLAB, Department of Pathology, Medicum, HUS Gynecology and Obstetrics, Department of Obstetrics and Gynecology, and Clinicum
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0301 basic medicine ,Cancer Research ,endocrine system diseases ,Medizin ,PROTEIN ,Genome-wide association study ,Carcinoma, Ovarian Epithelial ,VARIANTS ,THERAPY ,DISEASE ,Cohort Studies ,Models ,Ovarian Epithelial ,MAPT ,WIDE ASSOCIATION ,GWAS ,2.1 Biological and endogenous factors ,Aetiology ,Cancer ,Ovarian Neoplasms ,Regulation of gene expression ,Women's cancers Radboud Institute for Molecular Life Sciences [Radboudumc 17] ,Tumor ,Methylation ,female genital diseases and pregnancy complications ,Ovarian Cancer ,3. Good health ,Oncology ,CpG site ,Urological cancers Radboud Institute for Health Sciences [Radboudumc 15] ,DNA methylation ,Female ,Life Sciences & Biomedicine ,Risk ,SUSCEPTIBILITY LOCI ,3122 Cancers ,Oncology and Carcinogenesis ,Biology ,Article ,White People ,03 medical and health sciences ,All institutes and research themes of the Radboud University Medical Center ,Rare Diseases ,Genetic ,Predictive Value of Tests ,Clinical Research ,Genetic model ,Biomarkers, Tumor ,Genetics ,medicine ,Humans ,Genetic Predisposition to Disease ,Oncology & Carcinogenesis ,Epigenetics ,Science & Technology ,Models, Genetic ,IDENTIFICATION ,Prevention ,Carcinoma ,Human Genome ,DNA Methylation ,medicine.disease ,030104 developmental biology ,TISSUE ,Cancer research ,Women's Health ,1112 Oncology And Carcinogenesis ,Biomarkers - Abstract
DNA methylation is instrumental for gene regulation. Global changes in the epigenetic landscape have been recognized as a hallmark of cancer. However, the role of DNA methylation in epithelial ovarian cancer (EOC) remains unclear. In this study, high-density genetic and DNA methylation data in white blood cells from the Framingham Heart Study (N = 1,595) were used to build genetic models to predict DNA methylation levels. These prediction models were then applied to the summary statistics of a genome-wide association study (GWAS) of ovarian cancer including 22,406 EOC cases and 40,941 controls to investigate genetically predicted DNA methylation levels in association with EOC risk. Among 62,938 CpG sites investigated, genetically predicted methylation levels at 89 CpG were significantly associated with EOC risk at a Bonferroni-corrected threshold of P < 7.94 × 10−7. Of them, 87 were located at GWAS-identified EOC susceptibility regions and two resided in a genomic region not previously reported to be associated with EOC risk. Integrative analyses of genetic, methylation, and gene expression data identified consistent directions of associations across 12 CpG, five genes, and EOC risk, suggesting that methylation at these 12 CpG may influence EOC risk by regulating expression of these five genes, namely MAPT, HOXB3, ABHD8, ARHGAP27, and SKAP1. We identified novel DNA methylation markers associated with EOC risk and propose that methylation at multiple CpG may affect EOC risk via regulation of gene expression. Significance: Identification of novel DNA methylation markers associated with EOC risk suggests that methylation at multiple CpG may affect EOC risk through regulation of gene expression.
- Published
- 2019